An Efficient Profile Matching Protocol Using Privacy Preserving in Mobile Social Network

AbstractAs we know user profile matching with privacy-preservation in mobile social networks (MSNs) and bring in a family of novel profile matching protocols. We first intend an explicit Comparison-based Profile Matching protocol (eCPM), that runs between parties, initiator, and a responder. It is to propose modified an implicit Comparison-based Profile Matching protocol (iCPM) which allows the initiator to obtain directly some messages instead of the comparison result from the responder. The messages unrelated to user profile can be divided into multiple categories by the responder. The initiator implicitly chooses the open category that is unknown to the responder. The responder prepares two messages in each category, and the initiator can obtain only one message according to the similarity result on a single attribute. Then further, generalize the iCPM to an implicit Predicate-based Profile Matching protocol (iPPM) which allows complex similarity criteria spanning multiple attributes. The secrecy analysis shows all these protocols achieve the privacy of user profiles. Also, the eCPM reveals the similarity result to the initiator, and provides only relative anonymity; the iCPM and the iPPM do not disclose the outcome at all and provide full anonymity (secrecy). It is to analyze the communication overhead and the anonymity strength of the protocols. Then present an enhanced version of the eCPM, called eCPM+, by combining the eCPM with a novel prediction-based adaptive pseudonym change strategy. The performance of the eCPM and the eCPM+ are comparatively studied through extensive trace-based simulations. Simulation results show that the eCPM+ achieves significantly higher anonymity strength with a slightly larger number of pseudonyms than the eCPM